We published a paper based on extending Within-Cluster Resampling (WCR) to paired resampling in order to permit cluster-specific inference. An affected and an unaffected individual are sampled from each cluster (e.g. family) and compared with regard to covariates by fitting a paired-data logistic regression model. The paired resampling is repeated many times and the separate estimates pooled. When the response to an exposure varies across clusters, due to unmeasured modifiers, usual approaches become invalid, but WCPR remains valid. In two related projects, we developed a statistical test for unmeasured effect modification, and are also developing an approach for analysis of the case-crossover study, a design used to study effects of shared, time-varying environmental exposures, such as air pollution.